Abstract
In this research, a novel food recommendation system is presented for recommending a proper calorie daily food for an overweighed person to gain a healthy body status by using his or her Body Mass Index (BMI), Basal Metabolic Rate (BMR), k-Nearest Neighbors (k-NN) algorithm, and a back-propagation neural network (BPNN). The system estimates the overweight status of a person by using the BMI value. By using the BMR value, the system calculates the Daily Needed Food calories (DNC) of a person. The k-NN algorithm selects a proper calorie daily food set from the food dataset by using the saturated value of the DNC as its test object. The system predicts the days required for a person to gain a healthy BMI status with the recommended food by using overweight and saturated DNC values. Finally, the system evaluates its user’s satisfaction level based on the BPNN. The presented food recommendation system could be an effective way of propagating healthy weight awareness among common people.
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References
K.G. Anilkumar, Recommended weight prediction system based on BMI, BMR, food calorie and a neural network, in 2nd International Conference on Intelligent Informatics and BioMedical Sciences (ICIIBMS 2017) (IEEE, Okinawa, Japan, 2017), pp. 15–22
https://www.geeksforgeeks.org/k-nearest-neighbours Last accessed 30 Jan 2020
https://stackabuse.com/k-nearest-neighbors-algorithm-in-python-and-scikit-learn. Last accessed 3 Feb 2020
B. Wolfgang, N. Peter, E.K. Robert, D.F Frank, Genetic Programming An Introduction (Morgan Kaufmann Publishers, San Francisco, 1998)
L.P. David, A.K. Mackworth, Artificial Intelligence Foundations of Computational Agents, 2nd edn. (Cambridge University Press, Cambridge, 2018)
M. Negnevitsky, Artificial Intelligence-A Guide to Intelligent Systems, 2nd edn. (Addison Wesley, Boston, 2005)
S. Russell, P. Norvig, Artificial Intelligence: A Modern Approach, 2nd edn. (Pearson Education, New Jersey, 2004)
V.B. Rao, H.V. Rao, Neural Networks & Fuzzy Logic (BPB Publications, New Delhi, 1996)
https://www.nhlbi.nih.gov/health/educational/lose_wt/BMI/bmicalc.htm. Last accessed 4 Feb 2020
https://medium.com/analytics-vidhya/how-to-build-a-restaurant-recommendation-engine-part-2-71e2d0721084. Last accessed on 8 Feb 2020
C. Pathanjali, E.S. Vimuktha, G. Jalaja, A. Latha, A comparative study of Indian food image classification using k-NN and SVMs. Int. J. Eng. Technol. 7(3.12), 521–525 (2018)
N.S. Sabounchi, H. Rahmandad, A. Ammerman, Best fitting prediction equations for basal metabolic rate: informing obesity interventions in diverse populations. Int. J. Obes. (London) 37(10), 1364–1370 (2013)
T.K. Abdel-Hamid, Modeling the dynamics of human energy regulations and its implications for obesity treatment. Syst. Dyn. Rev. 18(4), 431–471 (2002)
https://www.healthline.com/nutrition/how-many-calories-per-day#intake-averages. Last accessed 13 Feb 2020
K.J. Rothman, BMI-related errors in the measurement of obesity. Int. J. Obes. (London) 32, 56–59 (2008)
https://www.healthstatus.com/calculate/body-mass-index/. Last accessed on 2 Feb 2020
https://www.sharecare.com/group/sharecare-fitness. Last accessed on 9 Feb 2020
https://www.sciencedaily.com/terms/basal_metabolic_rate.htm. Last accessed on 1 Feb 2020
https://catalog.data.gov/dataset/mypyramid-food-raw-data-f9ed6. Last accessed on 30 Jan 2020
K.G. Anilkumar, A subjective job scheduler based on backpropagation neural network. Hum. Centric Comput. Inf. Sci. (HCIS) (A Springer Open Journal) 3(1), 17 (2013). https://doi.org/10.1186/2192-1962-3-17
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Gopalakrishnan, A.K. (2021). A Food Recommendation System Based on BMI, BMR, k-NN Algorithm, and a BPNN. In: Joshi, A., Khosravy, M., Gupta, N. (eds) Machine Learning for Predictive Analysis. Lecture Notes in Networks and Systems, vol 141. Springer, Singapore. https://doi.org/10.1007/978-981-15-7106-0_11
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DOI: https://doi.org/10.1007/978-981-15-7106-0_11
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